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AFRICAN UNION

UNION AFRICAINE

UNIÃO AFRICANA

Statistics Division Economic Affairs Department

A Draft Statistical Quality Assurance Framework for the African Statistics System

May 2015

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Acronyms

ABS Australian Bureau of Statistics

ACS African Charter on Statistics

AEC African Economic Community

AIA African Integration Agenda

ASS African Statistics System

AU African Union

AUC African Union Commission

CoDG Committee of Directors-General

DFID Department for International Development (UK)

EUROSTAT Statistical Office of the European Commission

GSBPM Generic Statistical Business Process Model

DQAF Data Quality Assessment Framework

ICT Information and communications technology

IMF International Monetary Fund

ISO International Organisation for Standardisation

METIS Statistical Metadata

NQAF National Quality Assurance Framework

NSDS National Strategy for the Development of Statistics

NSO National Statistical Offices

NSS National Statistics System

OAU Organisation of African Unity

OECD Organisation for Economic Cooperation and Development

ONS Office for National Statistics (UK)

SASQAF South African Statistical Quality Assessment Framework

SHaSA Strategy for the Harmonisation of Statistics in Africa

STATAFRIC African Union Institute for Statistics

SVC Statistical Value Chain

UN United Nations

UNECE United Nations Economic Community for Europe

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1 Introduction

The main outcome of the establishment of the African Union Institute for Statistics (STATAFRIC) is accurate

reporting on the state of the African Integration Agenda (AIA) in terms of the economy of the continent and life

circumstances of the continent’s inhabitants. The main objective of STATAFRIC is to facilitate production and use

of good quality statistics to inform development initiatives in the political, economic, and social and cultural areas

constituting the African Integration Agenda (AIA). The outcome of the AIA will be the African Economic Community

(AEC). The statistics will play their traditional role of establishing programme and intervention baselines, setting

performance targets, identifying indicators for monitoring progress (or lack thereof) made by programmes and/or

projects, and assessing impact and outcomes. It is well established that African statistics are beset with constraints

on availability, quality and capacity1. This report is focused on the quality issue: to develop a framework for

assuring the quality of the statistics produced by the African Statistics System (ASS) used to inform the AIA.

Resolution to the quality issue is an imperative for the African Statistics System it has to achieve one of its

objectives expressed in SHaSA as Strategic Theme 1: to produce quality statistics for Africa.

In order to attain buy-in from the 54 member states and other stakeholders, a collaborative effort and wide

participation will be required to finalise the framework. Wide participation will also provide an opportunity to include

issues that may be unique to individual member states or regional blocks that might be omitted in the proposed

framework. Therefore this report ought to be treated as a working document for some entity such as the Committee

of Directors-General (CoDG) to take forward and finalise; an alternative approach can be defined by the

Department of Economic Affairs at AUC. Once the generic framework is finalised, the process of adaption by

member states should then commence.

2 Background

With the attainment of political independence, at an individual level, every African country has formulated

development policies, implemented development programmes and projects, and undertaken interventions where

programmes have been seen to falter in order to promote socioeconomic development. At the same time energies

have been expended on regional and continental integration. Since the formation of the Organisation of African

Unity (OAU) 51 years ago, African countries have strived to integrate their economies as well as their diverse social

and cultural entities within a single overarching political framework. However, while these efforts can be said to

have reached various levels of success, Africa is still the least developed continent.

One of the main reasons for Africa’s slow pace of development are a lack of the culture of managing for results

characterised by hazy accountability and limited transparency in development programme definition, planning,

implementation and management. The lack of accountability and transparency is due to the low profile of statistics

throughout practically all African countries. The problem is the dearth of reliable statistical information with sufficient

coverage and quality to guide planning and decision-making, and to measure the performance of development

programmes.

Practically all African countries have weak statistics systems which are mostly fragmented resulting in the low

profile of statistics in the public service environment. One immediate reason for the weak systems is ineffective

legislation which, in most cases, is about the national statistics office (NSO) rather than the national statistics

system (NSS). Where legislation includes the NSS it grants the NSO, which is the usual coordinating authority,

oversight responsibility but no power to coordinate production and dissemination of statistics. As a result, the

coordinating authority has no control over how other agencies in the NSS produce and disseminate statistics.

Another reason, not publicised but presumably constrained by political correctness, is the discomfort caused to

political principles when statistics tell an unfavourable story. This is more or so the case when the coordinating

authority reports to a minister or other cabinet functionary.

1 African Union Commission, African Development Bank and United Nations Economic Commission for Africa, 2010. See reference

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The low profile of statistics in the public service environment maintains itself in some form of steady state through

exclusion from the national plan and low prioritisation in state funding. Statistics budgets are perennially

insufficient, being traditionally underfunded by the government and relying on donor funding. Statistical links with

the national plan are usually tenuous and unidirectional from the NSO to the plan. The NSDS is not organically

developed but donor driven, and may be aligned but not integrated with the national plan. Participation in the NSDS

by agencies other than the NSO is limited to the preparatory and design phases as there is limited participation

during the implementation phase. As already indicated, substantive programme funding is donor-driven. Even then

allocation of donor funding among competing needs is not balanced. Only 2 percent of donor funding is allocated to

statistics on the basis of donor preferences. Of the 2 percent, most goes to health issues and household surveys.

As a result, very little funding is available to do the bulk of statistical work.2 In addition, national budgets are mostly

decentralised, with only NSO budgets being regarded as budgets for statistics.

The low profile of statistics in the public service environment has resulted in the following facts:

patchy production resulting in insufficient stock of statistics (information gap);

poor or unknown quality of available and yet-to-be produced data due to lack or non-application of

internationally acceptable quality frameworks (quality gap);

insufficient human resources & infrastructure (capacity gap);

limited role of statistics in national development agendas (low profile);

externally driven demand for statistics;

nationally underfunded statistical production;

high levels of dependency on donor funding;

under- & over-reporting of phenomena (e.g. education statistics); and

issues of legitimacy, reliability and trust.

The current international debate on the quality of African Statistics leaves one relatively confused. The state of

African statistics is seen as poor and misleading3to some;, it is tragic to others4; and it is transitional to yet others5.

Each of the three positions contain certain truths but not the whole truth. What is important is that they are

expressions of mistrust in and illegitimacy of African statistics. What needs to be done is to move African statistics

to a position of trust and legitimacy.

Notwithstanding the unsatisfactory current state of African statistics, there are initiatives in or being put into place to

improve the quality and stock of the statistics. The African Charter on Statistics (provision of an overarching

framework for quality development), SHaSA (defining the African statistics programme), NSDS (for comprehensive

planning for national statistics), ICT programme (to improve national accounts), capacity building by Pan-African

organisations, African Data Consensus (for demand-driven and open data, harnessing data to impact on

development decision-making and on building a culture of usage, to grant independence to NSOs), etc.

The thrust of the debate on African statistics is about quality, which makes the development and implementation of

a quality assurance framework an imperative for improvement of statistics of the African Statistics System.

Meaning of statistical quality

Based on ISO 9000 quality may be defined as the extent or degree to which materials, products, processes and

services meet pre-specified standards (requirements, specifications, guidelines or characteristics) defined to serve

a pre-defined purpose. Alternatively quality refers to the extent or degree to which materials, products, processes

and services are fit for their purpose. Thus

“The quality of an object can be determined by comparing a set of inherent characteristics against a set of

requirements. If those characteristics meet all requirements, high or excellent quality is achieved but if those

2 Trayler-Smith, A., 2015 reporting on Amanda Glassman; see reference 3 Jerven, M., 2013; see references 4 Devarajan, S., 2013; see reference 5 Kiregyera, B., see reference

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characteristics do not meet all requirements, a low or poor level of quality is achieved. So the quality of an object

depends on a set of characteristics and a set of requirements and how well the former complies with the latter.”

(ISO 9000)

With regard to official statistics, statistical quality refers to four interrelated perspectives all of which should be

taken into account when producing statistics. These are:

organisational context;

characteristics of the statistical product;

user’s perception of the statistical product; and

the statistical production process.

Organisational context

The organisational context provides an enabling environment for the production and use of official statistics. Within

the African Statistics System the enabling environment is at the AU member state level. It is generally the case that

within member states official statistics have a low profile in terms of use and supply by the state. At the moment the

context within which statistics are produced and consumed needs a lot of improvement. As already indicated, it is

characterised by insufficient data whose quality is either poor or unknown relative to international standards.

Demand for official statistics is best met when all the agencies that produce statistics for the state are organised

into a system such that their work is coordinated from a central point to standardise production processes, and

rationalise products and their use. The trend within the African Statistics System to establish NSSs comprising

mainly of statistics-producing state agencies should ideally meet the need for statistics systems. Coordination of

the NSS, setting up of standards, and rationalisation of production are expected to be led by the national statistics

office (NSO).

The NSS is expected to be coordinated by the national statistics office (NSO) which, in most member states is the

only agency statutorily mandated to produce official statistics. While the majority of users look up to the NSO to

meet their demand for statistics, the NSO is insufficiently capacitated to meet the demand either in terms of

quantity or in terms of quality. In any case the NSO on its own is unlikely ever to be in a position to meet the

overwhelming demand for official statistics as it is neither likely nor desirable to have the required human and

infrastructural capacity to produce either the quantity or variety of good quality statistics needed by the state and

other users. The overwhelming gap in the supply of official statistics has to be filled by a national effort - by other

organs of state according to their mandates. Yet efforts by other agencies in the NSS to provide statistics are much

weaker, many of them being unaware of the potential of their administrative systems to provide the statistics they

require to fulfil their mandates. They look to the NSO, private sector vendors, private sector contractors and

international organisations to meet their requirements for statistics.

Thus NSSs are either weak or exist only in name mainly because of the weak coordination mechanisms at the

disposal of the NSO. Key coordinating instruments for the NSS include, among others,

statistical legislation (both primary and subordinate);

a head of the government statistical system;

quality management frameworks, including common (shared) standards and quality assurance and

assessment frameworks

statistical planning (NSDS);

statistical clearing house;

a professionalised body of official statisticians;

statistics fora;

code of ethics;

technical support (capacity building);

training; and

a management system for statistical information (harmonised databases)

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However, for over a decade there are indications that there has been an increase in demand for statistics followed

by increasing advocacy to raise the profile of statistics. International and Pan-African Organisations have been at

the forefront of the advocacy drive by promoting various initiatives notably establishment and strengthening of the

various coordinating mechanisms. Among the coordinating instruments emphasis has been given to the National

Strategy for the Development of Statistics (NSDS), quality frameworks (e.g. the Charter) and statistical capacity

building programmes.

This report is developing a quality assessment framework which constitutes a part of the one constituent of the

quality management framework, one of the NSS coordinating instruments.

Characteristics of the statistical product

Characteristics of the quality of a statistical product are called quality components, quality criteria, or quality

dimensions. While in advanced economies quality frameworks (incorporating quality dimensions) have become an

integral part of the culture of statistical quality assurance, such frameworks have as yet to be adopted by the

majority of developing economies including the so-called middle income countries. African countries such as

Ethiopia, Rwanda, Seychelles, and South Africa, among others, are gradually adapting international frameworks to

assure the quality of their official statistics. The adaptations are founded on IMF’s DQAF and its various derivatives

especially Statistics Canada’s Quality Assurance Framework and the Quality Assurance Framework of the

European Statistical System. However, evidence of the extent of their implementation in the assessment for quality

of statistical products is not readily available. What has previously happened in some cases is the engagement of

consultants to assess products using DQAF.

User’s perception of the statistical product

It is important that data quality dimensions also cover users’ actual perceptions of the quality of a statistical

product. This explains why the internationally adopted definition of statistical quality, originating from Statistics

Canada, is defined as “fitness for use”6 or its variant “fitness for purpose”7 as is the case with the Office for National

Statistics (ONS) in the UK and the Australian Bureau of Statistics (ABS)8 (2009). The definition is from the point of

view of the user. Thus in terms of statistical outputs quality refers to the degree to which the data meet user needs.

Legitimacy of statistical information depends both on the quality of the underlying statistics and the trust users have

in the statistics. Both the quality of statistics and the trust that users have in them are a direct reflection on the

agency that produces them. The reputation of the agency determines the level of trust of the statistics it produces.

Practically all statistical quality frameworks and codes of practice, especially the UN’s Fundamental Principles of

Official Statistics and the NQAF, highlight the importance of institutional factors as the basic foundation for

statistical quality. Accordingly commitment of the leadership of a statistical agency to pursuing quality and to

creating a culture in which quality is recognised as a cornerstone of statistical work is a must.

Quality of data can rarely be explicitly ‘measured’. While quality components remain the same, in many cases

users will almost always perceive product quality differently from a statistics-producing organ of state (statistical

authority). The difference is one of emphasis on components. In general users tend to emphasise two as indicators

of a given set of statistical data. These are data comparability and coherence and timeliness (including frequency)

of data production. Furthermore, some of the quality components are difficult to assess by the user. For example,

user may give less priority to accuracy than to timeliness; may not be sufficiently literate to assess the quality of

certain components, such as accuracy, without expert support; or may not be informed of the components at all.

This is a communication issue for the producer of statistics to take cognizance of. There is a challenge here:

statistics producers appear to be more producer-oriented than user-oriented relative to the ease of access by

statistically unsophisticated users. This is often reflected in the difficulty the majority of statisticians encounter, of

6 Statistics Canada, 2002 7 Office of National Statistics, 2007 8 Australian Bureau of Statistics (ABS)8 (2009)

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communicating what they produce to users. Statistics producers need to deal with both the real and the perceived

quality of their products, which is not standard practice at the moment.

Statistical production process

The production process is a fundamental determinant of product quality. Different process designs prioritise

different product quality components, for example the trade-off between accuracy and budget or accuracy and

timeliness. This means that no process design will maximise all product quality components at any given time.

While there is no standard definition for the production process as is the case with product quality, the statistical

value chain (SVC) provides an effective framework for the process. The internationally agreed generically

standardised SVC is part of a broader statistical business process model finalized by a Joint

UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS) in 20099. Typical process variables include

resources used (inclusive of time), response burden or rates, error rates such as those in data capture and editing,

etc.

3 Quality assurance framework

The quality assurance framework for the African Statistics System defines the standards and indicators against

which African statistics have to be assessed. The standards and procedures are closely aligned to the Principles of

the African Charter on Statistics which incorporates the UN’s Fundamental Principles of Official Statistics, IMF’s

Data Quality Assessment Framework (DQAF), Quality Assurance Framework of the European Statistical System,

Statistics Canada’s Quality Assurance Framework, Australian Bureau of Statistics (ABS) Data Quality Framework,

Statistics Finland’s Quality Guidelines for Official Statistics, and Statistics South Africa’s Statistical Quality

Assessment Framework (SASQAF), among others. Accordingly, it meets the desired international quality

standards.

The framework is very closely aligned with the African Charter on Statistics (ACS) as it is the instrument to

implement the Charter. The Charter’s six principles constitute quality dimensions as indicated below:

1. Professional independence;

2. Quality;

3. Mandate for data collection and resources;

4. Dissemination

5. Protection of individual data, information sources and respondents 6. Coordination and Cooperation

As given in the Charter, each one of the principles are sub-divided into sub-principles. Elements whose quality are

to be assured have been identified for each sub-principle. Indicators have also been identified for each element to

provide evidence that the quality of the element has or has not been assured. In the majority of cases there is more

than one indicator to an element10. In the Annex the framework has been matched against the UN’s Guidelines for

the Template for a Generic National Quality Assurance Framework (NQAF). While there is limited one-on-one

correspondence between the elements of the two frameworks, the contents of the proposed framework is covered

by the content in the template.

9 Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS). Generic Statistical Business Process Model, Version 4.0, April 2009. Brussels: UNECE Secretariat, April 2009. Available at http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+Final.pdf?version=1 PDF version; http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+v4.0.doc?version=1 Word version; and http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM.ppt?version=1 PowerPoint Presentation at ISI in Durban, August 2009. 18 February 2012 10 Statistics South Africa, 2012: see references

http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+Final.pdf?version=1

http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+v4.0.doc?version=1

http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM.ppt?version=1

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Table 1: A Generic Statistical Assurance Framework for the African Statistics System

Principle 1: Professional independence

Description: Professional Independence means statistics authorities operate without any due influence from interest groups to ensure credible statistics

Sub-principle Elements to be assured Indicators

1.1: Scientific independence

Description: Statistics

authorities must be able to

carry out their activities

according to the principle of

scientific independence,

particularly vis-à-vis the

political authorities or any

interest group; this means that

the methods, concepts and

nomenclatures used in

statistical operation shall be

selected only by the statistics

authorities without any

interference whatsoever and

in accordance with the rules of

ethics and good practice

1.1.1a Independence of production and dissemination of statistics

from interference and/or influence by any individual, interest group

or political authority is specified in law

1.1.1b Conflict of the statistics law with any other law in terms of

rules, regulations, official policies, and procedures must be resolved

in favour of the statistics law

1.1.1.1a Legislation is in place that unambiguously

guarantees development, production, dissemination and use

of statistics without interference from political authorities or

any other interest group. The legislation must also define the

roles and responsibilities of other statistical agencies in the

national statistics system.

1.1.1.1b Mechanisms are in place for resolving conflicts

between the statistical law with any other piece of legislation

1.1.2 Mechanisms (policies, procedures, protocols, subordinate

legislation) are in place and are publicly known to ensure the

statistics authority’s exclusive and full control over the production

and dissemination of statistics with regard to decisions on statistical

methods, standards and procedures, content and timing of

statistical releases

1.1.2.1 There is in place a publicly known or well publicised

statistical value chain for both surveys and registers

independently defined by the statistics authority without

interference from any individual, interest group or political

authority

1.1.3 Mechanisms exist for the statistics authority to ensure that

professional ethics and good practice are adhered to during

production and dissemination of statistics

1.1.3.1 A code of ethics or good practice to be adhered to

during the production and dissemination of statistics is in

place

1.1.4 Statistical releases are clearly distinguished and issued

separately from political/policy statements

1.1.4.1 A logo or trademark for statistical releases is in place

and publicly announced

1.2 Impartiality


authorities shall produce,

analyse, disseminate, and

comment on African statistics

in line with the principle of

1.2.1 The principle of impartiality in dissemination of statistics is

specified in statistical legislation

1.2.1.1 A clause in the statistics law providing for impartiality

during release of statistics

1.2.2 Statistical production, analysis and dissemination are

undertaken without bias towards any individual, interest group or

political authority

1.2.2.1 A policy document is available for public information

outlining the procedures the statistics authority follows in its

production, analysis and dissemination of statistics;

and outlining the standard content of publications and

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scientific independence, and

in an objective, professional,

transparent, neutral and

unbiased manner in which all

users get equal treatment

inclusion of metadata with the statistical releases

1.2.3 Statistical information is normally released impartially. Pre-

sight of statistical information under embargo is announced publicly

1.2.3 A protocol on the release procedure ensuring

impartiality to all stakeholders is in place and published

1.2.4 The statistics authority comments publicly on any statistics

and/or statistical issues; such comments may include criticism on

any aspect of the statistical value chain and interpretation and

misuse of official or national statistics

1.2.4.1 A policy is in place that unambiguously states the

right of the statistics authority to comment publicly on any

aspect of statistics (criticisms, misinterpretations and

misuses) released in the public domain

1.3 Responsibility


authorities and African

statisticians shall employ

unambiguous and relevant

methods in the collection,

processing, analysis and

presentation of statistical data.

Statistics authorities shall also

have the right and duty to

make observations on

erroneous interpretation and

improper use of the statistical

information that they

disseminate

1.3.1 Internationally established and/or peer-agreed relevant

methods are used in the collection, processing, analysis and

presentation of statistical data

1.31.1 Manual of statistical methodology aligned to

international best practice is in place

1.3.2 The statistics authority unfailingly corrects any

misinterpretation or any proper use of the statistics it is responsible

for

1.3.2.1 A programme is in place to convert statistics into

statistical information for users and the public at large to

minimise the possibility of misinterpretation

1.3.2.2 A users’ training programme is in place to ensure

correct interpretation of the statistics produced by the

statistics authority; and to explain what statistical estimation

entails

1.3.3 Every statistical release is accompanied with metadata in a

transparent manner

1.3.3.1 Metadata are described and together with quality indicators or measures are prepared and provided to users to help them assess the quality of the released data

1.4 Transparency

Description: To facilitate

proper interpretation of data,

statistics authorities shall

provide information on their

1.4.1 All phases of the statistical production cycle are documented

and the cycle is easily available to the public

1.4.1.1 Publish standardised manuals of the methodology

used in the collection, processing, analysis and presentation

of every statistical series

1.4.2 Procedures are in place to ensure standard concepts, definitions and classifications are consistently applied

1.4.2.1 Publish a manual of concepts and definitions of the

statistical value chain of both surveys and registers for easy

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sources, methods and

procedures that have been

used in line with scientific

standards. The domestic law

governing operation of the

statistical systems must be

made available to the public

access by the public

1.4.2.2 Publish classification systems used with various

surveys and registers

1.4.2.3 Publish a guide on the interpretation of the data used

and estimates of each statistical series

1.4.3 Access to statistical legislation is continuously promoted 1.4.3.1 Publish a simplified version of the statistics law for

easy access by the public

Principle 2: Quality

Description: Quality in Statistics means “fitness for purpose” to ensure usability of statistics


2.1 Relevance

Description: African statistics shall

meet the needs of users

2.1.1 External and internal users of statistics are

identified and listed

2.1.1.1 Compile a database of external and internal users

2.1.2 A process exists to identify user needs 2.1.2.1 Develop an instrument to assess user needs (e.g., a

questionnaire)

2.1.2.2 Execute a user needs survey at specified intervals (e.g., annually)

2.1.3 A process to measure user satisfaction

exists

2.1.3.1 Develop an instrument to assess user satisfaction (e.g., a

questionnaire)

21.3.2 Execute a user satisfaction survey at specified intervals (e.g.,

annually)

2.1.3.3 Include priorities based on user needs in statistical work

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programme

2.2 Sustainability


be conserved in as detailed as

possible a form to ensure their use

by future generations, while

preserving the principles of

confidentiality and protection of

respondents

2.2.1 Resources are available to sustain

production of statistics in the long term

2.2.1.1 The national budgetary process must ensure coverage of existing

statistical series and emerging issues based on national priorities

2.2.2 Appropriate technology is used to archive

microdata for time series analysis

2.2.2.1 Put in place information technology infrastructure for the archiving

and retrieval of data

2.2.3 Measures are in place to ensure the

confidentiality of microdata

2.2.3.1 Measures are place to ensure the confidentiality of microdata

2.3 Data sources

Description: Data used for

statistical purposes may be

collected from diverse sources

such as censuses, statistical

surveys and/or administrative

records. The statistics

organisations shall choose their

sources in consideration of the

quality of data offered by such

sources and their topicality,

particularly the costs incurred by

the respondents and sponsors. The

use by statistics authorities of

administrative records for statistical

purposes shall be guaranteed by

domestic law, provided that

2.3.1 Data sources – censuses, sample surveys,

registers - are specified in law in keeping with the

confidentiality requirement

2.3.1.1 Statistical legislation – both primary and subordinate – must define

a process for identifying and guaranteeing sources of statistics as

censuses, sample surveys or registers

2.3.2 A data quality tool is in place to assess the

quality of potential data sources and to guide their

selection for use

2.3.2.1 A data quality assessment tool exists to assess the quality of both

existing and potential statistical data sources

2.3.3 A system of reviewing statistical production

for contemporariness is in place

2.3.3.1 A process exists for reviewing the currency or contemporariness of

existing statistical series

2.3.4 A measure of the respondent burden is in

place and is used to reduce the burden in

successive surveys

2.3.4.1 Methods and practices exist to measure and reduce the burden to

respondents associated with all data collection ventures11

2.3.4.2 Targets are in place to reduce respondent burden and they are

established for each type of data collection venture

2.3.5 A process is in place for assessing the

efficiency of resources, particularly funding, with

2.3.5.1 Assess the efficiency of resources, particularly funding, in relation

11 Such methods and practices may include fully-fledged surveys or surveys on pilots specifically designed to measure respondent burden using a combination for example of

instrument length, participant attitudes on usefulness and privacy-invading nature of instrument items, survey media used, etc.

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confidentiality is preserved regard to topicality, respondent burden, and

sponsors

to allocation to the currency of priorities, respondent burden, and sponsors

2.3.6 A process is in place for data sharing among

statistics authorities

2.3.6.1 Put in place a process for data sharing among statistics authorities

2.4 Accuracy and reliability


be an accurate12 and reliable13

reflection of reality

2.4.1 Standards and any other measures of

assessment of accuracy are identified and applied

to the statistical estimation process

2.4.2 Standards and any other measures of

assessment of reliability are identified and applied

to the statistical estimation process

2.4.1.1 Include standards and any new measures of accuracy of statistical

estimates in the statistical quality assessment tool

2.4.1.1a For sample surveys the following are estimated and published:

sampling errors14; and

non-sampling errors15

2.4.1.1b For registers/frames the following are estimated and published:

measures of under-reporting

duplication (of records) rate

measure of comprehensiveness (missing data)

coding error rate

editing rate

editing failure rate

imputation rate of under-reporting

12 The accuracy of a statistical estimate refers to how close or how far the estimate is from the true value of the phenomena it is designed to measure 13 The reliability of a statistical estimate refers to the consistency of either a process or of an estimate over time and/or geographic space; that is, the closeness of an initial process result and/or estimate to subsequent process results and/or estimates. (For example re-test reliability is used to establish the reliability of fieldwork in a survey by comparing a re-test sample with the main sample) 14 Measures of sampling errors include: standard error; coefficient of variation (CV); confidence interval (CI); mean square error (MSE); and design effect (DEFF) 15 Measures of non-sampling errors that should be considered include: under-coverage; up-to-date correspondence between administrative units and statistical units; duplication rate; proportion of units out of scope on the sampling frame relative to the total units in the frame; proportion of misclassified units relative to the total units in the frame; effects of data collection instruments on the estimates; effects of mode(s) (methods) of data collection; effects of the interviewers; effects of respondents; rate of proxy response; data entry error rate; coding error rate; average editing rate; editing success rate; editing failure rate; item non-response rate; unit non-response rate; imputation rate for item non-response; imputation rate for unit non-response; record matching

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imputation rate of missing values

frequency of register/frame maintenance

measure of impact of frame maintenance

2.4.2.1 Reliability

Users are informed of the process used in the construction of the sampling frame and the state of its currency. Deficiencies in the frame should be revealed

Information is available on maintenance of the sampling frame including updating of births and deaths in the population

Information for the user on the sample design including sample size and which sampling methods were used

Processes engaged to reduce measurement error (e.g. questionnaire development, survey pilot, etc.) are comprehensively documented

Report on respondent feedback on difficulty (or otherwise) on responding to survey items and the solutions undertaken to the difficulty raised

Assessment of the bias in the information sought caused by items that are perceived as sensitive to the respondent

A description of the method used and the reason(s) why it was used are available to users

Method(s) of estimating variances are made available especially in cases where standard formulae are not readily applicable as is the case with complex or multistage sampling designs, mixed survey and register data designs and register data samples

2.4.3 Quality measures are in place to monitor the

statistical process, including product quality

2.4.3.1 A statistical value chain calibrated to appropriate levels is available 2.4.3.2 Quality measures are in place to monitor statistical activity at each phase of the statistical value chain 2.4.3.3 A documented and published quality management process is in place 2.4.3.4 A report of the assessment and validation of source data is available

2.4.4 Quality guidelines are in place 2.4.4.1 A quality assurance framework and its implementation guidelines

14




are in place

2.5 Continuity

Description: Statistical authorities

shall ensure continuity and

comparability of statistical

information over time

2.5.1 Standardised concepts and definitions,

classifications, methodology and frames are in

place to facilitate comparisons over time

2.5.1.1 A compendium of standardised concepts and definitions is published 2.5.1.2 A catalogue of agreed classifications, adapted to African realities, is published 2.5.1.3 A manual of common methodologies for specific statistical domains is published 2.5.1.4 A frame (such as a master sample) common and accessible to all agencies in the NSS is available 2.5.1.5 A plan to maintain (update) frames exists 2.5.1.6 Procedures are in place to monitor the application of standardised concepts, definitions and classifications in the NSS

2.6 Coherence and comparability

Definition: African statistics shall be

internally coherent over time and

allow for comparison between

regions and countries. To this end,

these statistics shall make

combined use of related data

derived from different sources. It

shall employ internationally

recognized and accepted concepts,

classifications, terminologies and

methods

2.6.1 Internationally recognised standards –

concepts, definitions, classifications, methodology

– have been adapted for data collection

2.6.1.1 (Refer to indicators 2.5.1.1 to 2.5.1.6)

2.6.2 A practice is in place to use common

standards and frames – and to ensure

consistency among datasets

2.6.2.1 A data harmonisation process through a coordination framework

with measures to monitor compliance in implementing common standards

and frames is in place and is enshrined in law

2.6.2.2 Methodological procedures and protocols are in place and

enshrined in law to ensure consistency among datasets in the NSS

2.6.3 A process is in place to ensure statistics are

internally coherent and consistent

2.6.3.1 Common statistics reporting units are defined and published

substantively and geographically including updates in the NSS

2.6.3.2 Protocols exist and are guaranteed in law to use common

concepts and harmonised methods for specified statistical outputs

2.6.3.3 Coherence and consistency between data produced at different

frequencies, same socioeconomic domain, and sources and outputs are

included in the quality assessment tool

2.6.4 A process is in place to ensure statistics are 2.6.4.1 Protocols exist and are guaranteed in law to use common

15




comparable across series or datasets concepts and harmonised methods for specified statistical outputs

2.6.3.2 Data comparability over time, across varying administrative

geographies, sector and sub-population level is included in the quality

assessment tool

2.6.5 A process is in place to ensure statistics are

coherent over a reasonable period of time

2.6.5.1 A minimum period for meaningful time series analysis is agreed

and implemented

2.6.6 A programme is in place to ensure cross-

national comparability of data within the provisions

of the African Statistical System

2.6.6.1 Prepare statistics on a sector basis to facilitate international

comparisons

2.6.6.2 Establish processes within the SHaSA framework to ensure

statistics are coherent and comparable, including across national

boundaries

2.7 Timeliness


be disseminated in good time and,

as far as possible, according to a

pre-determined calendar

2.7.1 Release dates, times and procedures are

announced before statistics are released

2.7.1.1 A pre-publication release calendar that includes release of

preliminary results of any data collection is centrally published

2.7.2 Any divergence from the dissemination time

schedule is publicised in good time, is explained,

and is rescheduled

2.7.2.1 Any divergence from the pre-publication calendar including the

new schedule is centrally published in advance and, where possible, with

sufficient lead time to inform clients

2.7.3 Preliminary results may be released when it

is deemed necessary to do so

2.7.3.1 Statistical production is aligned to the national policy cycle

2.7.4 Timeliness meets international

dissemination standards

2.7.4.1 International dissemination standards are adopted and published

for the entire NSS

2.8 Topicality

Description: African statistics shall reflect current and topical events

2.8.1 Statistics reflect current or contemporary

events

2.8.1.1 The work programme of the statistical authority incorporate the

needs of policy makers and users

2.8.2 Statistics are produced during the period

they are needed and can be actually used

2.8.2.1 A strategy is in place to monitor the turn-around time of statistical

results with the aim to reduce the period between the end of data

16




and trends collection and release of results

2.8.2.2 See indicator 2.7.3.1

2.8.3 A measure of topicality is in place and is

applied to statistical production

2.8.3 A measure of topicality is in place and is regularly applied to

statistical production

2.8.4 A process is in place for periodic reviews of

existing statistical series for contemporariness

2.8.4 A process (such as user fora, advisory or scientific committees) is in

place for reviewing statistical production for contemporariness

2.8.5 A process is in place for continuously

assessing the policy and user environments for

developments that may require new statistical

series

2.8.5 A process (such as a policy unit, a webpage for client feedback) is in

place for constantly monitoring changes or developments in policy and

user environments to identify gaps for new statistical series

2.9 Specificities

Description: Statistical data

production and analytical methods

shall take into account African

peculiarities

2.9.1 A database of statistics produced matched

against specific user needs exists

2.9.1.1 A compendium of indicators/indices is developed to pin down

specifically what users want and accordingly define the domain and scope

of statistical production

2.9.2 Statistical methods adapted to peculiar

African problems (such as enumeration in shack

settlements and the informal sector) have been

developed

2.9.2.1 A research and training programme is in place to adapt and/or

develop a methodology to deal with problems peculiar to African situations

2.10 Awareness building

Description: State Parties shall

sensitize the public, particularly

statistical data providers, on the

importance of statistics

2.10.1 An advocacy programme is in place to

raise the profile of statistics among politicians

2.10.1.1 A programme is in place to handpick key political personalities to

champion the use of statistics in managing for outcomes

2.10.1.2 A programme is in place to advocate for managing for results

among politicians with emphasis on measuring outcomes and

performance; and informing planning and decision-making

2.10.2 A training programme is in place for

advocacy and awareness building

2.10.2.1 A statistical market segmentation list of stakeholders exists to

facilitate communication

2.10.2.2 A training programme is in place for advocacy and awareness

17




building aiming at the identified segments of the statistical market

2.10.3 A programme is in place to train media in

the accurate interpretation of statistical output

2.10.3.1 A programme is in place to train the media on the accurate

interpretation of statistics

2.10.4 A programme is in place to promote

statistical literacy (culture) in the general

population

2.10.4.1 A programme is in place through media to promote statistical

literacy in the general population

2.10.4.2 Develop and implement a training programme to build capacity in

statistical skills at secondary and tertiary institutions

2.10.5 A programme is in place to promote a

culture of using statistics for evidence based

decisions

2.10.5.1 A programme is in place to advocate for using statistics for

evidence based decision-making

2.10.5.2 Statistical requirements in the national development plan are

incorporated into the statistical authority’s work programme

2.11 Statistical process

Description: Appropriate statistical

procedures covering the entire

statistical value chain must be

implemented beginning with the

need for data collection from either

a survey or a register and ending

with a review of the statistical

production process

2.11.1 A statistical value chain for surveys and

registers has been defined, implemented and

published for public access

2.11.1 Define, publish and implement a statistical value chain for both

surveys and registers16

2.11.2 A process is in place for prioritizing the

need for statistical information

2.11.2.1 A work programme that prioritises statistical needs in the national

development plan is in place

2.11.3 A process is established for designing the

statistical production activities

2.11.3.1 A process is in place for designing for statistical production

2.11.4 A process is in place for preparatory

(building) stage for fieldwork or data collection,

metadata, and documentation

2.11.4.1 A process is in place that defines the building stage

(preparations) for fieldwork or data collection

16 Or can adapt Joint UNECE/Eurostat/OECD’s Generic Statistical Business Process Model (GSBPM). Check reference

18




2.11.5 A process is in place for fieldwork or data

collection, metadata, and documentation

2.11.5.1 A process is in place for conducting fieldwork or data collection

2.11.6 Infrastructure and processes for data

processing are documented and in place

2.11.6.1 A process is in place for data processing

2.11.7 Processes for data analysis are in place 2.11.7.1 A process is in place for data analysis

2.11.8 Dissemination and publication principles

and procedures are documented and in place

2.11.8.1 A process is in place for data dissemination or data access

2.11.9 Infrastructure and processes for archiving

data are documented and in place

2.11.9.1 A plan exists for data archiving and retrieval

2.11.10 A process for evaluating the data

collection project is in place

2.11.10.1 A process is in place for evaluating statistical production project

2.11.11 A process is in place to test

questionnaires prior to data collection

2.11.11.1 A process is in place for testing questionnaires prior to data

collection

2.11.12 Survey designs, sample selection

methodology, and sample weighting methodology

are regularly reviewed, revised or updated

2.11.12.1 A process exists for regular reviews, revisions, or updates of

sample survey designs, sample selection methodology, and sample

weighting methodology

2.11.13 A process and documents are in place to

regularly review, maintain and revise the domain

of registers

2.11.13.1 A process exists to review, maintain and revise the domain of

registers on a regular basis

2.11.14 A process is in place to routinely monitor

and revise field operations and data processing

(data entry, coding and editing)

2.11.14.1 A process is in place to routinely monitor and revise field

operations, and data processing (data entry, coding and editing)

2.11.15 A transparent process is in place for

revisions

2.11.15.1 A schedule and a process is in place for revisions

19

Principle 3: Mandate for data collection and resources

Description: Mandate for data collection means the legal responsibility to collect data for statistical purposes. Resources means adequate, predictable and

sustainable funding to be provided by National Governments


3.1 Mandate

Description: Statistics authorities

shall be endowed with a clear legal

mandate empowering them to collect

data for production of African

statistics. At the request of statistics

authorities, public administrations,

business establishments,

households and the general public

may be compelled by domestic law

to allow access to the data in their

possession or provide data for the

purpose of compilation of African

statistics

3.1.1 The legal mandate to a statistics authority

to collect data is specified in the statistical

legislation

3.1.1.1 A statistics law is in place and provides NSS bodies with the

authority to collect data

3.1.2 The authority to access data or to receive

data from public administrations, the public

sector, households and the public at large is

specified in the statistics law

3.1.2.1 There is included in the statistics law authority for the statistics

authority to collect or access data from public administrations, the

private sector, households and the public at large

3.1.3 The obligation of respondents to provide

information is specified in the statistics law

3.1.3.1 There is included in the statistics law the obligation of

respondents to provide information

3.2 Resource adequacy

Description: As far as possible, the

resources available to statistics

authorities shall be adequate and

stable to enable them to meet

statistics needs at national, regional

and continental levels. Governments

of State Parties shall have the

primary responsibility to provide such

3.2.1 Staff, financial, and statistical infrastructure

are available within the official government

budgeting framework

3.2.1.1 A budget for statistics exists within the government’s

expenditure framework with sufficient funds for statistical skills,

infrastructure and operations for meeting the needs of users

3.2.2 The scope, detail, and cost of statistics are

commensurate with needs

3.2.1.2 The costing of statistical production in the work programme is

based on user needs

3.2.3 Specific training programmes are in place

to build basic and advanced statistical skills

3.2.1.3 A comprehensive statistics training programme is in place to

build basic and advanced statistical skills

20





resources

3.3 Cost effectiveness


shall use the resources so provided

effectively and efficiently. This

presupposes, in particular, that

operations shall as far as possible,

be programmed in an optimal

manner. Every effort shall be made

to achieve improved production and

use of the statistics derived from

administrative records, to reduce the

costs incurred by respondents and,

as far as possible, avoid expensive

direct statistical surveys

3.3.1 A process is in place to cost statistical

operations, human resources, and statistical

infrastructure across all state agencies

3.3.1.1 A system is in place for costing statistical production across all

state agencies

3.3.2 Strategic and operational plans exist to

effectively guide resource allocation

3.3.2.1 Strategic, action and operational plans are in place for the

production of statistics

3.3.2.2 A model is in place to guide optimal allocation of resources

among all state agencies that produce statistics

3.3.3 A strategy is in place to optimise resource

allocation and to minimise the reporting burden

by rationalising surveys through coordination

3.3.3.1 A coordination programme exists to optimise resource

allocation and minimise respondent burden by rationalising surveys

3.3.4 Data collection instruments are designed

such that they are respondent-friendly,

effectively collect information, and are efficient

3.3.4.1 Well designed and tested respondent-friendly data collection

instruments are in place

3.3.5 A quality management system is

implemented to improve data quality and

timeliness

3.3.5.1 Implement a quality management system to improve both data

quality and timeliness

3.3.6 A policy for preference for and increased

use of registers as sources of data and a

decreased reliance on surveys is implemented

3.3.6.1 There is in place a policy biased towards the use of

administrative records as a source of statistics

3.3.7 The use of administrative records for

statistical purposes is specified in statistical

legislation

3.3.7.1 Use of administrative records for statistical purposes is included

in the statistics law

3.3.8 A review programme for topicality to

determine discontinuation and/or inclusion of

3.3.8.1 A programme is implemented to monitor the currency of

existing programmes to determine their continuation or discontinuation

21





new series is in place and/or inclusion of new series

3.3.9 Internal and external measures are in

place to monitor the statistics authority’s use of

resources

3.3.9.1 Internal and external systems are set up to monitor use of

resources

3.3.10 Routine clerical operations (e.g., data

capture, coding and validation) are automated to

the extent possible

3.3.10.1 An ICT system is in place for automating as much as possible

routine clerical systems

3.3.11 Optimisation of the use of ICT whenever

possible for data collection, processing and

dissemination

3.3.11.1 ICT systems are in place for data collection, processing and

dissemination

Principle 4: Dissemination

Description: Dissemination means statistics are accessible, clear and usable without constraint


4.1 Accessibility


not be made inaccessible in any way

whatsoever. This concomitant right

of access for all users without

restriction shall be guaranteed by

domestic law. Micro-data may be

4.1.1 A policy document exists that

comprehensively spell out statistical

dissemination principles and practice, including

microdata subject to specified conditions

4.1.1 1 A document on statistical dissemination policy and practice is

published for the benefit of users and the public at large

4.1.1.2 Conditions for access to microdata are published

4.1.2 Right of equal and free access to data by

the public is included in the statistics legislation

4.1.2.1 A clause on right of equal and free access by the public is

incorporated in the statistics legislation

4.1.3 A list and synopsis of available statistics is 4.1.3.1 A list including synopses of statistics that are available in the

22




made available to users on condition

that the pertinent laws and

procedures are respected and

confidentiality is maintained

published and updated as required country is published

4.1.4 A system for managing user requests is in

place

4.1.4.1 A system in place to receive, process, archive and monitor user

requests

4.1.5 Statistics are available and accessible

according to market segmentation needs using

hardcopy and/or modern ICT

4.1.5.1 A list of classified users on the basis of market segmentation

according to the appropriateness of the medium used to access

statistics (e.g., electronic or hardcopy) is in place

4.1.5.2 There is in place a list of groups of users according to the

medium of data access suitable for them (e.g., by website, hardcopy,

etc.)

4.1.5.3 An internal protocol is in place identifying the appropriate

medium to be used for disseminating data to specified groups of users

identified during the market segmentation exercise

4.1.6 Statistical releases and statements made

in the media are objective and non-partisan

4.1.6.1 A policy and protocols are in place for guiding the statistics

authority to make objective, non-partisan statements in the media

4.2 Dialogue with users

Description: Mechanisms for

consultation with all African statistics

users without discrimination shall be

put in place with a view to ensuring

that the statistical information offered

are commensurate with their needs

4.2.1 Users are grouped according to their

needs

4.2.1.1 A list of users according to the statistical market segmentation

is in place

4.2.2 A process for user consultation is in place 4.2.2.1 A user consultation process on various statistical matters is

established

4.2.2.2 User fora are established according to user groups

4.2.2.3 A process is in place to establish user needs including

feedback on the suitability of statistical products

4.2.2.4 User needs impact on priorities, design of survey and statistical

products are documented

4.2.2.5 Statistical priorities based on user needs are documented and

23




included in the statistical work programme

4.2.3 User satisfaction surveys are undertaken

periodically

4.2.3.1 A programme of user satisfaction survey at least every two

years is in place

4.3 Clarity and understanding

Description: Statistics shall be

presented in a clear and

comprehensible form. They shall be

disseminated in a practical and

appropriate manner, be available

and accessible to all and

accompanied by the requisite

metadata and analytical

commentaries

4.3.1 Statistics are presented in a form that is

easily understood and interpreted

4.3.1.1 A standardised statistical release template, including provisions

for metadata and analytical commentaries is in place

4.3.2 Statistics are packaged in different format

appropriate for different groups of users

4.3.2.1 A process is in place for consulting different groups of users to

determine applicable formats required for disseminating results

4.3.2.2 A system is in place for developing different statistical products

per series according to user groups

4.3.3 Custom-designed analyses are provided

where appropriate

4.3.3.1 A protocol is in place for the provision of custom-designed

analytical support to meet special requests

4.3.4 Metadata and analytical commentaries are

made available and accessible to all users with

the statistical release

4.3.4.1 A tool is in place to facilitate capturing metadata

4.3.5 Users are informed on the methodology of

statistical processes and the quality of statistical

outputs

4.3.5.1 Information is published on the methodology of the statistical

process and quality of the statistical output

4.3.5.2 A data validation process is established

4.3.5.3 A training programme for data validation is in place

4.3.6 Users are educated in the use of statistics 4.3.6.1 A training programme exists for users on usage and

interpretation of statistics

4.4 Simultaneity

Description: African Statistics shall

be disseminated in a manner that

4.4.1 The principle of simultaneity of

dissemination of statistics is specified in

statistical legislation to ensure impartiality

4.4.1.1 A clause on simultaneity of release of statistical products is

incorporated in statistical legislation

24




ensures that all users are able to use

them simultaneously. Where certain

authorities receive advance

information under embargo, to allow

them time to respond to possible

questions, public announcement

shall be made indicating the nature

of such information, the identity of

the recipients and the set timeframe

before its public dissemination

4.4.2 Statistical information is normally released

to everyone at the same time. Pre-sight of

statistical information under embargo is

announced publicly

4.4.2.1 Conditions under which pre-sight is granted to users under

embargo and publicly announced are defined and published

4.4.3 Statistical release dates and times are

announced

4.4.3.1 A statistical release calendar is published annually

4.4.3.2 Any deviations from the release calendar are announced and

explained to users

4.4.3.3 Divergences from pre-announced times are published in advance, and new release times are announced with explanations of the reasons for the delays

4.5 Correction


shall correct publications containing

significant errors using standard

statistical practices or, for very

serious cases, suspend

dissemination of such statistics. In

that event, the users shall be

informed in clear terms of the

reasons for such corrections or

suspension

4.5.1 A policy document exits that details the

circumstances under which corrections to

publications are made

4.5.1.1 Publish a corrections policy in anticipation of an error in the

statistics produced by the statistics authority

4.5.2 A process is in place for corrections to

publications

4.5.2.1 A corrections policy is published in anticipation of an error in

the statistics produced by the statistics authority

4.5.3 Corrections to publications are announced

publicly

4.5.3.1 A policy is in place to define and publicly announce the type of

revision (e.g. preliminary, forecast)

4.5.3.2 A policy is in place to publish the corrections or announce

withdrawals of publications

4.5.4 A published policy is in place for revisions

to statistical series arising from small changes in

methodology and new data sources

4.5.4.1 A policy is in place on a process for making corrections to

publications including withdrawal of publications

4.5.5 A revision in methodology is announced

publicly

4.5.5.1 A revisions policy in anticipation of any changes in data

including methodology is in place

4.5.6 A revised methodology is published. 4.5.6.1 A policy is in place to publicly announce and publish the new

25




methodology

4.5.6.2 Explanations about the timing, reasons for and nature of

revisions are made available

4.5.6.3 A published policy is in place that describes the revisions for key outputs that are subject to scheduled revisions

Principle 5: Protection of individual data, information sources and respondents

Description: Protection of individual data, information sources and respondents means privacy and confidentiality are guaranteed


5.1 Confidentiality

Description: National statistics authorities,

African statisticians and all those operating in

the field of statistics in Africa shall absolutely

guarantee the protection of the private life

and business secrets of data providers

(households, companies, public institutions

and other respondents), the confidentiality of

the information so provided and the use of

such information for strictly statistical

purposes

5.1.1 Protection of the confidentiality of data

collected for official statistical purposes is

guaranteed in statistical legislation. The legislation

should include penalties for any willful breaches of

confidentiality

5.1.1.1 A confidentiality clause is included in the statistical

law; the clause must include penalties for any willful

breaches of confidentiality

5.1.2 A legal provision that binds staff to commit to

confidentiality is in place

5.1.2.1 A requirement is provided in the statistics law for

staff to take a confidentiality oath or sign legal

confidentiality commitments

5.1.2.2 Guidelines and instructions are in place for staff on the protection of statistical confidentiality in the production and dissemination processes

5.1.3 A policy document is available mapping out

arrangements for maintaining confidentiality of data

and for disseminating or providing access to data

5.1.3.1 A policy document is published mapping out

arrangements for maintaining the confidentiality of data and

for disseminating or providing access to data

26




5.2 Giving assurances to data providers

Description: Persons or entities interviewed

during statistical surveys shall be informed of

the objective of such interviews and of the

measures put in place to protect the data

provided

5.2.1 A system is in place for respondents to be

informed of the main intended uses and access

limitations applying to the information they provide

to statistical inquiries

5.2.1.1 A system to inform respondents of the main

intended uses and access limitations applying to the

information they provide is in place and published

5.2.2 Provisions are in place to protect the security

and integrity of statistical databases

5.2.2.1 Strict measures are in place to protect the security

and integrity of statistical data bases

5.3 Objective

Description: Data concerning individuals or

entities collected for statistical purposes shall

in no circumstance be used for judicial

proceedings or punitive measures or for the

purpose of taking administrative decisions

against such individuals or entities

5.3.1 A legislative guarantee is in place for

(individual) respondent data not being used for

judicial and punitive purposes or for the purpose of

taking administrative decisions against individuals

or entities except under the Statistics Act

5.3.1.1 A clause is included in the statistics law to ensure

protection of non-use of statistical data for judicial and

punitive purposes and taking administrative decisions

against individuals or entities

5.3.1.2 Codes of practice and standards are in place to

ensure that statistical data about individual respondents

remain confidential, and are only released to users in line

with statistical legislation and data dissemination policies

5.3.2 A programme is in place for creating

awareness in the legal system, among statisticians,

political entities, and data custodians that statistical

data are not to be used for legal proceedings or

punitive measures or for the purpose of taking

administrative decisions against individuals or

entities

5.3.2.1 A programme is implemented to create awareness

among statisticians, political entities, the general public and

data custodians not to use respondent data for legal or

punitive purposes or for the purpose of taking administrative

decisions against individuals or entities

5.4 Rationality

Description: Statistics authorities shall not

embark upon statistical surveys except

where pertinent information is unavailable

from administrative records or the quality of

such information is inadequate in relation to

5.4.1 A policy prioritising administrative records

over surveys subject to data quality considerations

is in place

5.4.1.1 A policy is in place prioritising use and improvement

of administrative records over surveys subject to data

availability and quality considerations

5.4.2 The principle of rationalisation of production of

statistics is specified in statistical legislation to

eliminate overlapping and duplication subject to

5.4.2.1 A rationality clause is included in statistical

legislation

5.4.2.2 A statistical clearing house or a process is in place

27




the quality requirements of statistical

information

data quality considerations for identifying and resolving cases of duplication of efforts in

the production of statistics

5.4.3 An inventory of statistical information for the

country is available

5.4.3.1 (Indicator 4.1.3.1)

5.4.4 A mechanism for approval of statistical plans

to produce official statistics is in place

5.4.4.1 A statistics clearing house is included in the

statistics law and is in place to execute a statistical approval

process for statistical production for the NSS

28

Principle 6: Coordination and Cooperation

Definition: Coordination and cooperation means Statistics authorities work together and share expertise to ensure synergy, unicity, quality and comparability of

statistics in the national and African statistics systems


6.1 Coordination

Description: Coordination and collaboration amongst Statistics authorities in a given country are essential in ensuring quality and harmonious statistical information. Similarly, coordination and dialogue amongst all Members of the African Statistical System are vital for harmonization, production and use of African statistics.

6.1.1 The principle of statistics coordination and

collaboration amongst statistics authorities is

specified in statistical legislation

6.1.1 Statistical coordination, collaboration among statistics

authorities, and designation of statistics as official are

included in statistical legislation

6.1.2 A mechanism for approval of statistics plans is

in place

6.1.2.1 A National Strategy for Development of Statistics

(NSDS) is in place

6.1.2.2 A statistics clearing house or a mechanism is in

place to approve the plans (See indicator 5.4.4.1)

6.1.3 Statistical work programmes are published

annually, and periodic reports describe the progress

made

6.1.3.1 A statistical planning, reporting and approval

process is established for approval

6.1.3.2 Action and annual statistical work programmes are

compiled from the NSDS

6.1.4 Statistical production processes for surveys,

censuses and administrative records are based on

common statistical standards

6.1.4.1 There is in place a framework for statistical

production from surveys, censuses and administrative

records

6.1.4.2 A consultation process is in place for implementing

new questionnaires used in modifying registers by organs

of state and for introducing new statistical classifications

6.1.5 Designation of statistics as official statistics

(good quality) is specified in statistical legislation

6.1.5.1 There is a clause in the statistics law requiring all

statistics for a public good to be designated as official

statistics (good quality)

6.1.6 A process for designating statistics as official

statistics (good quality) is published to inform

producers and users and the public at large

6.1.6.A process is in place for designating statistics as

official statistics directed at informing all producers and

users of statistics and the public at large

6.1.7 Statistics are designated as official statistics 6.1.7.1 There is in place a statistical quality assessment

framework and protocol for the designation of statistics as

29





(good quality) official

6.1.7.2 Conduct independent quality assessments/audits

6.1.8 A governance structure for statistical

coordination among organs of state is in place

6.1.8.1 Governance structures are in place for different

levels of government administration as well as other

stakeholders including cooperation with other AU member

states

6.1.8.2 The role of the national statistical office as the coordinator of the national statistical system is established in the statistics law

6.1.9 The production and use of official statistics is

used for “managing for results” and “transformation”

6.1.9.1 A programme is implemented for advocating for

managing for results in government

6.1.10 Statistics authorities subscribe to the

Principles of the African Charter on Statistics

6.1.10.1 A signed and ratified African Charter on Statistics

is adopted as the foundation for statistical quality assurance

by the statistics authority

6.1.11 Statistics authorities align statistical practice

to the African Statistical System, as prioritised

SHaSA

6.1.11.1 Country strategic plans and the NSDS are aligned

to the African Statistics System and SHaSA

6.1.11.2 Self-assessment is done on implementation of the

Principles of the African Charter on Statistics

6.1.11.3 A process for participating in the peer review

process is in place

6.1.12 Statistics is included in the National

Development Plan/National Planning framework as

a system of evidence

6.1.12.1 The National Development Plan/National Planning

framework includes statistics as a system of evidence

6.1.13 A function is established in the statistics 6.1.12.2 A statistical function/unit responsible for the NSS is

30





authority for statistical coordination of the NSS established in the NSO

6.1.14 A function is in place at Africa regional and

continental levels for statistical coordination and

harmonisation

6.1.14.1 A statistical function/unit responsible for

coordination and harmonisation at African regional and

continental levels is established in the NSO

6.2 Co-operation

Description: Bilateral and multilateral

statistics cooperation shall be encouraged

with a view to upgrading African statistics

production systems

6.2.1 A schedule exists of activities such as

meetings, events, conferences, workshops, training,

etc. for active participation in the African Statistics

System at regional, continental and global level

6.2.1.1 A programme for the statistics authority’s active

participation in African Statistics System at regional,

continental and global level is in place

6.2.2 A programme exists to upgrade African

statistics production systems at regional,

continental and global levels

6.2.2.1 A statistical production harmonisation programme is

in place to upgrade African statistics production systems at

regional, continental and global levels

6.2.3 A national mechanism to coordinate and

monitor aid-assistance is in place

6.2.3.1 NSDS is in place as a framework for handling aid-

assistance requirements for development of statistics in the

NSS

6.2.3.2 NSDS is set up as a mechanism to coordinate and

monitor aid assistance for statistical production in the NSS

6.2.4 An aid-assistance reporting system is in place 6.2.4.1 Monitoring and reporting (of inputs, outputs and

outcomes) system of the implementation phase of the

NSDS is in place to monitor and report on aid-assistance

6.2.5 A cooperation model consistent with aid

effectiveness is in place

6.2.5.1 A centralised Statistics Fund is established for the

NSS

31

4 References

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Strategy for the Harmonisation of Statistics in Africa, Addis Ababa, Ethiopia

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Australian Bureau of Statistics, 2009, ABS Data Quality Framework, May. Accessed at

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2015

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September

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for Health Statistics, Hyattsville, MD 20782

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2015

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context of an establishment survey, Statistics Canada, Ottawa

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by the News Media and Government Contractor Survey Research Firms, in Advances in Telephone Survey

Methodology by Lepkowski, J. M., Clyde Tucker, C., J. Michael Brick, J., Leeuw, E. de, Japec, L., Lavrakas, P. J.,

Link, M. W. and Sangster, R. L., John Wiley & Sons, Inc.

International Monetary Fund, 2003, Data Quality Assessment Framework (DQAF), July. Available at

http://dsbb.imf.org/images/pdfs/dqrs_factsheet.pdf on 3 May 2015

Independent Expert Advisory Group on a Data Revolution for Sustainable Development (IEAG), 2014, A world that

counts: Mobilising the data revolution for sustainable development, United Nations Statistics Commission, New

York, November. Available at http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-

Counts2.pdf on 6 May 2015

International Organisation for Standardisation (ISO), 2012, Quality Management Principles, ISO Central

Secretariat, Geneva. Accessed at http://www.iso.org/iso/qmp_2012.pdf on 27 March 2015

Jäckle, A., Roberts, C. and Lynn, P., 2010, Assessing the effect of data collection mode on measurement,

International Statistics Review Vol. 78, No.1, pp 3-20

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Cornell University Press, Ithaca

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http://www.statistics.gr/portal/page/portal/ESYE/BUCKET/General/Quality_Assurance_ESS_v11_en.pdf%20on%2008%20May%202015

http://dsbb.imf.org/images/pdfs/dqrs_factsheet.pdf

http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf

http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf

http://www.iso.org/iso/qmp_2012.pdf

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Jerven, M, and Johnston, D., 2015, Statistical tragedy in Africa? Evaluating the database for African economic

development, The Journal of Development Studies, Vol. 51, No. 2, pp 111-115

Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS). Generic Statistical Business Process

Model, Version 4.0, April 2009. Brussels: UNECE Secretariat, April 2009. Available at

http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+Final.pdf?version=1 PDF version;

http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM+v4.0.doc?version=1 Word version;

and http://www1.unece.org/stat/platform/download/attachments/8683538/GSBPM.ppt?version=1 PowerPoint

Presentation at ISI in Durban, August 2009. 18 February 2012

Kale, Y., 2015, Where are the numbers? Presentation to a conference on African Economic Development:

Measuring Success and Failure, Simon Fraser University, Vancouver, Canada. Available at

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System-Vancouver-April-2013-FN-small4.pdf on 12 May 2015

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http://mortenjerven.com/wp-content/uploads/2013/04/AED_Panel_8-Kiregyera.pdf on 6 May 20152014; on 6 May

2014

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21, No. 2, pp. 233–255

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September

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in Establishment Surveys – BLS (Bureau of Laboor Statistics) and Census Bureau, presentation to the Federal

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Statistical Association, Vol. 87, No. 418, pp. 376–382, June

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(NQAF), United Nations Statistics Division, New York, 8 February

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33

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34

5 Annex

Matching the Generic Quality Assurance Framework for the African Statistics System against the UN’s Generic

National Quality Framework Template (NAQF)

Key items in the Generic Quality Assessment Framework for the African Statistics System

UN’s Generic National Quality Assurance Framework Template (NQAF)

Principle 1: Scientific independence

1.1 Scientific independence NQAF4 Assuring professional independence (independence of production and

dissemination of statistics is specified in law; conflict of the statistics law with any

other law must be resolved in favour of the statistics law; professional ethics and

good practice are adhered to during production and dissemination of statistics)

NQAF 5 Assuring impartiality and objectivity (independence of production and

dissemination of statistics is specified in law; professional ethics and good practice;

statistical releases are clearly distinguished and issued separately from political/policy

statements)

1.2 Impartiality NQAF 5 Assuring impartiality and objectivity (principle of impartiality is specified in

statistical legislation; statistical production, analysis and dissemination without bias)

NQAF 6 Assuring transparency (statistical information is normally released impartially.

Pre-sight is announced publicly)

1.3 Responsibility NQAF 5 Assuring impartiality and objectivity (international methods)

NQAF 6 Assuring transparency (release of metadata)

NQAF 8 Assuring the quality commitment (release of metadata)

NQAF 14 Assuring relevance (release of metadata)

NQAF15 Assuring accuracy and reliability (Internationally established and/or peer-

agreed relevant methods are used)

NQAF 17 Assuring accessibility and clarity (release of metadata)

NQAF 4 Assuring professional independence (correcting misinterpretation)

1.4 Transparency NQAF 6 Assuring transparency (production cycle documented)

NQAF 17 Assuring accessibility and clarity (production cycle documented)

NQAF 10 Assuring methodological soundness (concepts, definitions and classifications

constantly applied)

NQAF 13 Managing the respondent burden (concepts, definitions and classifications

constantly applied)


2.1 Relevance NQAF14 Assuring relevance

35



2.2 Sustainability NQAF 17 Assuring accessibility and clarity (archive)

NQAF 18 Assuring coherence and comparability (time series)

2.3 Data sources NQAF15 Assuring accuracy and reliability (data sources)

2.4 Accuracy and reliability NQAF15 Assuring accuracy and reliability

2.5 Continuity NQAF 10 Assuring methodological soundness (concepts and definitions standards)

2.6 Coherence and comparability NQAF 18 Assuring coherence and comparability

2.7 Timeliness NQAF 5 Assuring impartiality and objectivity (release dates, times and procedures)

NQAF 14 Assuring relevance (reflection of current or contemporary events)

NQAF 16 Assuring timeliness and punctuality (release dates, times and procedures)

2.8 Topicality NQAF 14 Assuring relevance (reference period)

NQAF 16 Assuring timeliness and punctuality (reference period)

NQAF 14 Assuring relevance (periodic reviews of existing statistical series)

NQAF 8 Assuring the quality commitment (continuous assessment of policy and user

environments)

2.9 Specificities NQAF 17 Assuring accessibility and clarity (A database of statistics produced matched

against specific user needs exists)

1. Quality context; 1a Circumstances and key issues driving the need for quality

management (paragraph 1:” adaptations according to … specific national

circumstances” for “Statistical methods adapted to peculiar African problems”)

2.10 Awareness building NQAF 13 Managing the respondent burden (advocacy and awareness building)

NQAF 2 Managing relationships with data users and data providers (training media in

the accurate interpretation of statistical output)

NQAF 14 Assuring relevance (culture of using statistics for evidence based decisions,

evaluation)

2.11 Statistical process NQAF 8 Assuring the quality commitment (statistical value chain for surveys and

registers, prioritising need for statistical information, designing the statistical

production activities, for preparatory (building) stage for fieldwork or data collection,

process is in place for fieldwork or data collection, data processing, data analysis,

dissemination, archiving, evaluation)

NQAF 11 Assuring cost-effectiveness (statistical value chain for surveys and registers)

NQAF 2 Managing relationships with data users and data providers (process for

designing the statistical production activities)

NQAF 10 Assuring methodological soundness (designing the statistical production

36



activities, evaluation, testing questionnaires)

NQAF 12 Assuring soundness of implementation (statistical value chain for surveys

and registers, process for fieldwork or data collection, data processing, archiving,

evaluation, testing questionnaires)

NQAF 9 Assuring adequacy of resources (data analysis, dissemination)

NQAF 19 Managing metadata (dissemination, archiving)

NQAF 1 Coordinating the national statistical system (dissemination, evaluation)

NQAF 4 Assuring professional independence (dissemination)

NQAF 5 Assuring impartiality and objectivity (dissemination)

NQAF 6 Assuring transparency (dissemination, transparent process for revisions)

NQAF 17 Assuring accessibility and clarity (dissemination policy, archiving)

NQAF 16 Assuring timeliness and punctuality (dissemination, evaluation)

NQAF 11 Assuring cost-effectiveness (evaluation)

NQAF 13 Managing the respondent burden (testing questionnaires, reviewing survey

methodology)

NQAF 14 Assuring relevance (evaluation, reviewing survey methodology)

NQAF15 Assuring accuracy and reliability (evaluation, transparent process for

revisions)


3.1 Mandate NQAF 2 Managing relationships with data users and data providers (legal mandate,

authority to access data, obligation to provide data, resource adequacy)

NQAF 13 Managing the respondent burden (obligation to provide data)

NQAF 16 Assuring timeliness and punctuality (obligation to provide data)

3.2 Resource adequacy NQAF 9 Assuring adequacy of resources (resource adequacy; staff, financial, and

statistical infrastructure resources are budgeted for; process is in place to cost

statistical operations, human resources, and statistical infrastructure)

NQAF 10 Assuring methodological soundness (plans to guide resource allocation;

optimise resource allocation)

NQAF 11 Assuring cost-effectiveness (resource adequacy)

3.3 Cost effectiveness NQAF 11 Assuring cost-effectiveness (preference for and increased use of registers as

sources of data and a decreased reliance on surveys; preferred use of administrative

records; respondent burden management; process to cost statistical operations,

human resources, and statistical infrastructure; programme for topicality to

37



determine discontinuation and/or inclusion of new series; external measures to

monitor statistics authority’s use of resources; automation of routine clerical

operations; optimised use of ITC)


4.1 Accessibility NQAF 4 Assuring professional independence (equal and free access to data by the

public statistics legislation)

NQAF 5 Assuring impartiality and objectivity (policy document on statistical

dissemination principles and practice; Statistical releases and statements made in the

media are objective and non-partisan)

NQAF 17 Assuring accessibility and clarity (system for managing user requests; list of

available statistics is published and updated)

4.2 Dialogue with users NQAF 2 Managing relationships with data users and data providers (list of users

according to market segmentation; process for user consultation)

NQAF 8 Assuring the quality commitment (satisfaction surveys are undertaken

periodically)

NQAF 12 Assuring soundness of implementation (process for user consultation)

4.3 Clarity and understanding NQAF 2 Managing relationships with data users and data providers (users informed

on methodology of statistical processes and quality of statistical outputs)

NQAF 5 Assuring impartiality and objectivity (analytical commentaries are made

available and accessible to all users with the statistical release; provision of

methodology)

NQAF 6 Assuring transparency (metadata made available to the public)

NQAF 7 Assuring statistical confidentiality and security (metadata made available to

the public)

NQAF 8 Assuring the quality commitment (metadata made available to the public;

provision of information on quality of statistical outputs)

NQAF 14 Assuring relevance (statistics are packaged in different formats appropriate

for different groups of users; metadata made available to users; users informed of

quality of statistical outputs)

NQAF 16 Assuring timeliness and punctuality (users informed on quality of statistical

outputs)

NQAF 17 Assuring accessibility and clarity (statistics are presented in a form easily

understood and interpreted; dissemination formats for different groups of users;

custom-designed provided on request; metadata made available to users; users

informed on methodology of statistical releases; users informed about quality of

statistical outputs)

NQAF 18 Assuring coherence and comparability (users informed on methodology of

statistical products)

38



4.4 Simultaneity NQAF 5 Assuring impartiality and objectivity (principle of simultaneity of

dissemination of statistics; pre-sight of statistical information under embargo is

announced publicly; release dates and times are announced; deviations from the

release calendar announced and justified to users; a revision in methodology is

announced publicly)

NQAF 6 Assuring transparency (release calendar and changes announced to the

public)

NQAF15 Assuring accuracy and reliability (a revision in methodology is announced

publicly)

NQAF 16 Assuring timeliness and punctuality (release dates and times are announced;

deviations from the release calendar announced; principle of simultaneity of

dissemination of statistics; revisions in methodology are announced; revised

methodology is published)


5.1 Confidentiality NQAF 2 Managing relationships with data users and data providers (processes in

place to assure statistical confidentiality of individuals, businesses or other entities in

administrative records)

NQAF 6 Assuring transparency (legislation protecting the confidentiality of individual

responses)

NQAF 7 Assuring statistical confidentiality and security (legal arrangements in place to

protect data confidentiality including penalties for wilful breaches of the law; policy

document available mapping out arrangements for maintaining confidentiality of

data)

NQAF 12 Assuring soundness of implementation (a legal provision binding staff to

commit to confidentiality is in place)

5.2 Giving assurances to data

providers

NQAF 6 Assuring transparency (respondents understand the legal basis for a survey and the confidentiality provisions for the data that are collected)

NQAF 7 Assuring statistical confidentiality and security (provisions are in place to

protect the security and integrity of statistical databases; a legal provision binding

staff to commit to confidentiality)

NQAF 13 Managing the respondent burden (a system in place for respondents to be

informed of the main intended uses and access limitations applying to the

information they provide)

5.3 Objective NQAF 7 Assuring statistical confidentiality and security (a legislative guarantee is in place for (individual) respondent data not being used for judicial and punitive purposes or for the purpose of taking administrative decisions against individuals or entities except under the statistics law)

5.4 Rationality NQAF 1 Coordinating the national statistical system (principle of rationalisation of

production of statistics is specified in statistical legislation to eliminate overlapping

and duplication subject to data quality considerations

39



NQAF 11 Assuring cost-effectiveness (policy prioritising administrative records over

surveys subject to data quality considerations)

NQAF 12 Assuring soundness of implementation (policy prioritising administrative

records over surveys subject to data quality considerations)

NQAF 13 Managing the respondent burden (policy prioritising administrative records

over surveys subject to data quality considerations)

NQAF 17 Assuring accessibility and clarity (An inventory (catalogue) of statistical

information for the country is available)


6.1 Coordination NQAF 1 Coordinating the national statistical system (a governance structure for

statistical coordination among organs of state is in place; principle of statistics

coordination and collaboration amongst statistics authorities is specified in statistical

legislation)

NQAF 4 Assuring professional independence (statistical work programmes are

published annually, and periodic reports describe the progress made)

NQAF 10 Assuring methodological soundness (statistical production processes for

surveys, censuses and administrative records are based on common statistical

standards)

NQAF 13 Managing the respondent burden (statistical production processes for


standards)

NQAF 14 Assuring relevance (a function is in place at Africa regional and continental

levels for statistical coordination and harmonisation)

NQAF 18 Assuring coherence and comparability (statistical production processes for


standards)

6.2 Co-operation NQAF 14 Assuring relevance (a schedule exists of activities … for active participation

in the African Statistics System at regional, continental and global level; programme is

in place to upgrade African statistics production systems at regional, continental and

global levels)

NQAF 2 Managing relationships with data users and data providers (a cooperation

model consistent with aid effectiveness is in place)

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